plasma microrna profiling reveals loss of endothelial mir

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DOI: 10.1161/CIRCRESAHA.110.226357 2010;107;810-817; originally published online Jul 22, 2010; Circ. Res.

Shah, Johann Willeit and Manuel Mayr Prokopi, Agnes Mayr, Siegfried Weger, Friedrich Oberhollenzer, Enzo Bonora, Ajay Anna Zampetaki, Stefan Kiechl, Ignat Drozdov, Peter Willeit, Ursula Mayr, Marianna

MicroRNAs in Type 2 DiabetesPlasma MicroRNA Profiling Reveals Loss of Endothelial MiR-126 and Other

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Clinical/Translational Research

Plasma MicroRNA Profiling Reveals Loss of EndothelialMiR-126 and Other MicroRNAs in Type 2 Diabetes

Anna Zampetaki,* Stefan Kiechl,* Ignat Drozdov, Peter Willeit, Ursula Mayr, Marianna Prokopi, Agnes Mayr,Siegfried Weger, Friedrich Oberhollenzer, Enzo Bonora, Ajay Shah, Johann Willeit, Manuel Mayr

Rationale: MicroRNAs (miRNAs) have been implicated in the epigenetic regulation of key metabolic, inflamma-tory, and antiangiogenic pathways in type 2 diabetes (DM) and may contribute to common disease complications.

Objective: In this study, we explore plasma miRNA profiles in patients with DM.Methods and Results: Total RNA was extracted from plasma samples of the prospective population-based

Bruneck study. A total of 13 candidate miRNAs identified by microarray screening and miRNA networkinference were quantified by quantitative PCR in all diabetic patients of the Bruneck study and age- andsex-matched controls (1995 evaluation, n�80 each). Quantitative PCR assessment revealed lower plasma levelsof miR-20b, miR-21, miR-24, miR-15a, miR-126, miR-191, miR-197, miR-223, miR-320, and miR-486 inprevalent DM, but a modest increase of miR-28-3p. Findings emerged as robust in multivariable analysis andwere independent of the standardization procedure applied. For endothelial miR-126, results were confirmed inthe entire Bruneck cohort (n�822) in univariate (odds ratio [95% confidence interval], 0.38 [0.26 to 0.55];P�2.72�10�7) and multivariate analyses (0.57 [0.37 to 0.86]; P�0.0082). Importantly, reduced miR-15a,miR-29b, miR-126, miR-223, and elevated miR-28-3p levels antedated the manifestation of disease. Mostdifferences in miRNA levels were replicated in plasma obtained from hyperglycemic Lepob mice. High glucoseconcentrations reduced the miR-126 content of endothelial apoptotic bodies. Similarly in patients with DM, thereduction of miR-126 was confined to circulating vesicles in plasma.

Conclusions: We reveal a plasma miRNA signature for DM that includes loss of endothelial miR-126. These findingsmight explain the impaired peripheral angiogenic signaling in patients with DM. (Circ Res. 2010;107:810-817.)

Key Words: diabetes mellitus � microRNA � vascular endothelium

MicroRNAs (miRNAs) are a class of small noncodingRNAs that function as translational repressors. They

bind through canonical base pairing to a complementary sitein the 3� untranslated region of their target mRNAs and candirect the degradation or translational repression of thesetranscripts.1–2 MiRNAs have been shown to play importantroles in development, stress responses, angiogenesis, andoncogenesis.3– 4 Accumulating evidence also points to animportant role of miRNAs in the cardiovascular system.4 –5

For example, miRNAs modulate endothelial cell functionand regulate their inflammatory response and angiogenicpotential.6 –7

Recently, Mitchell et al highlighted the presence of miR-NAs in plasma.8 These plasma miRNAs are not cell-associated, but packaged in microvesicles that protect them

from endogenous RNase activity. Interestingly, plasma miR-NAs can display unique expression profiles: specific tumormiRNAs were identified in cancer patients,9 whereas tissue-derived miRNAs constitute a marker for injury.10–11 Incardiovascular diseases, circulating miRNAs have been in-vestigated in myocardial injury, coronary artery disease, andheart failure.12–15 Type 2 diabetes mellitus (DM) is one of themajor risk factors of cardiovascular disease leading to endothelialdysfunction and micro- and macrovascular complications.16–17

However, a systematic analysis of plasma miRNAs in DM has notyet been performed.

The present study is the first to reveal a plasma miRNAsignature for DM in a large population-based cohort. Ourfindings may provide new insights into the pathophysiologyof DM and the manifestation of its vascular complications.

Original received June 16, 2010; revision received July 11, 2010; accepted July 13, 2010. In June 2010, the average time from submission to firstdecision for all original research papers submitted to Circulation Research was 14.5 days.

From the King’s College London British Heart Foundation Centre (A.Z., I.D., U.M., M.P., A.S., M.M.) and Centre for Bioinformatics-School ofPhysical Sciences and Engineering (I.D.), King’s College London, United Kingdom; Department of Neurology (S.K., P.W., J.W.), Medical UniversityInnsbruck, Austria; Department of Public Health and Primary Care (P.W.), University of Cambridge, United Kingdom; Department of LaboratoryMedicine and Department of Internal Medicine (A.M., S.W., F.O.), Bruneck Hospital, Italy; and Division of Endocrinology and Metabolic Diseases(E.B.), University Hospital of Verona, Italy.

*Both authors contributed equally to this work.Correspondence to Dr Manuel Mayr, King’s British Heart Foundation Centre, King’s College London, 125 Coldharbour Lane, London SE5 9NU,

United Kingdom. E-mail [email protected]© 2010 American Heart Association, Inc.

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MethodsAn expanded Methods section is available in the Online DataSupplement at http://circres.ahajournals.org.

Study SubjectsThe Bruneck study is a prospective population-based survey initiallydesigned to investigate the epidemiology and pathogenesis of ath-erosclerosis and later extended to study all major human diseasesincluding DM.18–20 At the baseline evaluation in 1990, the studypopulation was recruited as a sex- and age-stratified random sampleof all inhabitants of Bruneck (Bolzano Province, Italy) 40 to 79 yearsold. During 1990 and the re-evaluation in 1995 (the first five-yearperiod), a subgroup of 63 individuals died or moved away. In theremaining population follow-up was 96.5% complete (n�822). RNAextraction was performed from plasma specimens collected as part ofthe 1995 follow-up in 822 individuals. Follow-up in 2000 and 2005was 100% complete for clinical end points and �90% complete forrepeated laboratory examinations. Assessment of the ankle-brachialindex and incident peripheral artery disease is described in detail inthe Online Data Supplement. The Bruneck population is highlyrepresentative of the general community and shows characteristicssimilar to those of other Western countries. The mean age was 62.9years, 49.9% were women and the prevalence of DM was 9.7%.Their clinical characteristics are summarized in Online Table I. Theprotocols of the Bruneck study were approved by the appropriateEthics Committees, and all study subjects gave their written in-formed consent before entering the study.

Ascertainment of DMPresence of DM was established according to World Health Orga-nization criteria, ie, when fasting glucose was �7 mmol/L (126mg/dL) or when the 2-hour oral glucose tolerance test glucose levelwas �11.1 mmol/L (200 mg/dL) or when the subjects had a clinicaldiagnosis of the disease. Self-reported DM status was obligatorilyconfirmed by reviewing the medical records of the subject’s generalpractitioners and files of the Bruneck Hospital (for details, see theOnline Data Supplement).

MiRNA Expression ProfileRNA extraction was performed using the miRNeasy kit (Qiagen)from plasma specimens collected as part of the 1995 follow-up in822 individuals. MiRNAs were reverse-transcribed using the Mega-plex Primer Pools (Human Pools A v2.1 and B v2.0), and expressionwas screened using TaqMan miRNA Arrays A and B (all fromApplied Biosystems). TaqMan miRNA assays were used to deter-mine the expression of individual miRNAs. Additional details areprovided in the Online Data Supplement.

Sampling Strategy and Statistical AnalysisFor the initial microarray screening, 2 pools of plasma obtained from5 individuals with DM each (randomly selected from the 80 patientswith DM in the Bruneck study) and 6 pools of plasma obtained fromcontrols identical in age, sex, risk factor profile (low-density lipopro-tein, smoking, hypertension), and atherosclerosis status were used.Quantitative (q)PCR was performed for the 13 miRNAs that showedcorrelation with DM. TaqMan assays were run in duplicates. Twogroups of patients were assessed: group 1, all subjects with manifestDM in the Bruneck cohort (1995, n�80); group 2, 19 patients whodeveloped DM between 1995 and 2005 (incident DM). Eighty and19 matched individuals identical for age and sex with fasting glucoselevels of �6.1 mmol/L (110 mg/dL), 2-hour glucose of�7.7 mmol/L (140 mg/dL), and no history of DM served as controls.In the case of several suitable matches, all were numbered inascending order and one was selected by means of a computer-basedrandom number generator. Finally, miR-126 was measured in theentire population of 822 individuals. For the lack of generallyaccepted standards all qPCR data were analyzed as unadjusted Ctvalues and standardized to both miR-454 and RNU6b, a smallnuclear RNA, which fulfilled the following criteria: detectable in allsamples, low dispersion of expression levels and null associationwith DM status. Moreover, the miR-454 expression profile showedlittle association with other miRNAs and positioned outside thecoexpression modules of the complex miRNA network in plasma(Figure 1). Data were analyzed using SPSS version 15.0 and STATAversion 10 software packages. Continuous variables were presentedas means�SD or median (interquartile range) and dichotomousvariables as numbers and percentages. Fold changes of individualmiRNAs were calculated for each pair of matched (pre)diabetic casesand controls by dividing the standardized expression levels of the

Non-standard Abbreviations and Acronyms

CI confidence interval

CLR context likelihood of relatedness

DM type 2 diabetes

HUVEC human umbilical vein endothelial cell

Lepob Leptin obese

miRNA microRNA

PCA principal component analysis

PCC Pearson correlation coefficient

qPCR quantitative PCR

VEGF vascular endothelial growth factor

Figure 1. MiRNA coexpression networkand miRNA topology values. A,Weighted and undirected miRNA coex-pression network. Nodes correspond tomiRNAs and edges (links) indicate simi-larity in miRNA expression, as measuredby the PCC. Strength of similarity is indi-cated by a red-blue edge color gradi-ent. At PCC values of �0.85, the coex-pression network consisted of 120miRNAs and 1020 coexpression links. B,Relationships of node degrees (numberof coexpressing pairs for each miRNA),clustering coefficients (likelihood ofmiRNA sharing a large number of neigh-bors), and eigenvector centralities (rela-tive contribution of miRNA to stability ofthe network) for 120 miRNAs. There were

30 differentially expressed miRNAs (blue), of which 13 (red) occupied locations important to maintenance of the overall networkstructure.

Zampetaki et al Plasma MicroRNAs in Diabetes 811



miRNAs. The median of fold changes is presented in Figure 2.Differences in miRNA levels between subjects with prevalent orincident DM and corresponding groups of matched controls wereanalyzed using the nonparametric Wilcoxon test for related sampleswith computation of exact probability values. To account for thepotential confounding effects of lifestyle features and other variablesrelated to DM and to analyze for interactions, we additionallyperformed logistic regression analyses for matched data that includeloge-transformed expression levels of miRNAs (1 per model) and thefollowing variables: social status, family history of DM, body massindex, waist-to-hip ratio, smoking status, alcohol consumption (g/d),physical activity (sports index), and high-sensitivity C-reactiveprotein. Details on model construction were described by Hosmerand Lemeshow.21 First-order interactions between miRNAs and theabove variables, as well as age and sex, were calculated by inclusionof appropriate interaction terms. None of these terms achievedstatistical significance. Cox proportional hazard models were used toassess the predictive value of miR-126 for new-onset peripheralartery disease. Participants who experienced an outcome event werecensored with respect to subsequent follow-up. The proportionalhazard assumption was confirmed for miR-126 by testing theinteraction of miR-126 with a function of survival time (Cox modelswith time-dependent covariates). A total of 37 subjects with symp-tomatic peripheral artery disease at baseline were excluded, leaving785 subjects for this analysis. The potential association betweenmiR-126 and low ankle–brachial index was analyzed by means oflogistic regression analysis. This analysis was fit to the entire studypopulation. Differences in miR-126 between categories of glucosetolerance were compared with General Linear Models. All probabil-ity values presented are 2-sided.

MiRNA Coexpression Network Inferenceand AnalysisNetwork inference algorithms were applied to evaluate globalexpression properties of miRNAs in DM. Similarity in miRNAexpression profiles was interrogated using either Pearson correlationcoefficients (PCCs) or context likelihood of relatedness (CLR)between all possible miRNA pairs.22 Pairs that maintained depen-dence above a predefined threshold were represented in the formof an undirected weighted network, where nodes correspond tomiRNAs and links (edges) correspond to the similarity betweenthem. Although PCC is a way to measure linear relationshipsbetween features (miRNAs), CLR relies on a mutual informationmetric and does not assume linearity,23–24 thus possessing someflexibility to detect biological relationships that may otherwise bemissed. PCC was used to detect clusters of similarly expressedmiRNAs from a high throughput space of expression arrays, whereasCLR was used to identify all nonrandomly associated qPCR-validated miRNA profiles. Although PCC and CLR sometimes yieldsimilar results, CLR was chosen for qPCR-validated miRNAsbecause it is more sensitive to nonlinear dynamics of miRNAexpression than PCC and significantly outperforms other networkinference methods (eg, ARACNE) in identifying biologically mean-ingful relationships.25–26 The PCC threshold was set to a point wheremiRNA coexpression network began to acquire a scale-free archi-tecture, which is a characteristic of most real-world networks,including biological ones.27 To ensure reproducibility, the 30 differ-entially expressed miRNAs were evaluated by assessing their net-work properties,28 rather than the magnitude of over- or underex-pression. The CLR threshold was chosen such that all 13 miRNAscould be represented in the network while retaining the smallestpossible number of links between them.

Topological AnalysisDuring prescreening, miRNAs were studied by virtue of theirtopology in the global miRNA coexpression network, as well asindividual over- or underexpression. For each miRNA, topologicalparameters including node degree, clustering coefficient, and eigen-vector centrality were systematically calculated. Node degree isdefined as the total number of edges that are connected to a given

miRNA. Clustering coefficient is the degree to which miRNAs tendto cluster together. Eigenvector centrality is a measure of miRNAimportance, such that a particular miRNA receives a greater value ifit is strongly correlated with other miRNAs that are themselvescentral within the network.

Endothelial Cell CultureHuman umbilical vein endothelial cells (HUVECs) were purchasedfrom Cambrex and cultured on gelatin-coated flasks in M199medium supplemented with 1 ng/mL endothelial cell growth factor(Sigma), 3 �g/mL endothelial growth supplement from bovineneural tissue (Sigma), 10 U/mL heparin, 1.25 �g/mL thymidine, 5%FBS, 100 �g/mL penicillin and streptomycin as described previo-usly.29,30 HUVECs exposed to high glucose (25 mmol/L) werecultured in complete medium for 6 days. As a control, HUVECswere cultured in complete medium (5 mmol/L glucose) supple-mented with mannitol, to exclude effects of osmotic stress. On day5, cells were counted and an equal number of cells was seeded onT75 flasks and incubated for an additional day.

Isolation of VesiclesVesicles were isolated as described previously.31 In brief, HUVECswere deprived of serum and growth factors for 24 hours before theconditioned medium was harvested and the cells were lysed inQIAzol reagent. The cellular lysates were stored at �20°C formiRNA expression analysis. The conditioned medium was firstprecleared by centrifugation for 10 minutes at 800g to remove anyfloating cells. Then, endothelial particles (apoptotic bodies) wereisolated by centrifugation at 10 600 rpm for 20 minutes. Subse-quently, an additional centrifugation step was performed at 20 500rpm for 2 hours to isolate small microparticles (size, �1 �m)shedding from endothelial cells. Identical centrifugation stepswere performed to obtain vesicles from plasma. The pelletedvesicles were resuspended in PBS and stored at �80°C. TotalRNA was extracted using the miRNeasy kit as described above.RNA was quantified using the NanoDrop spectrophotometer and20 ng of total RNA were used for reverse transcription.

ResultsComprehensive MiRNA ProfilingFor the initial screening, Human TaqMan miRNA arrays(CardA v2.1 and CardB v2.0, Applied Biosystems) covering754 small noncoding RNAs were applied to 8 pooled sam-ples, 2 consisting of subjects with DM, and 6 of appropriatecontrols (see methods). Of the 148 miRNAs with Ct values of�36, 130 miRNAs were detected using fluidic Card A andtherefore all further analysis focused on this data set, resultingin the identification of 30 differentially expressed plasmamiRNAs in patients with DM (Online Table II).

MiRNA Network AnalysisMiRNA pairs with high correlation values (PCC �0.85) wererepresented in the form of an undirected and weightednetwork. At this threshold, the network was dominated by asmall number of hubs that linked with many loosely con-nected nodes, a property of many biological networks (OnlineFigure I). The miRNA network consisted of 120 miRNAs(nodes) and 1020 coexpression links (edges) (Online TableII). The 30 differentially expressed miRNAs were sampled byvirtue of their localization in the miRNA coexpressionnetwork as marker selection using network topology is morereproducible than assessment of individual over- or underex-pression.28 Within the network, the 30 differentially ex-pressed miRNAs were topologically central (Online FigureII; Online Table III). 13 of the 30 differentially expressed

812 Circulation Research September 17, 2010



miRNAs that displayed extreme spectra of node degrees,clustering coefficients, and eigenvector centrality values wereselected (Figure 1B). MiR-454 was the only miRNA thatshowed no association with the expression of other miRNAsand was positioned outside all network modules (Figure 1A).Thus, it was chosen as an additional normalization control.

Validation by qPCRThe 13 topologically unique miRNAs were further quantifiedby qPCR. All patients with manifest DM at the time of the1995 evaluation (n�80) were compared to age- and sex-matched controls (Online Table I). Plasma levels of miR-24,miR-21, miR-20b, miR-15a, miR-126, miR-191, miR-197,miR-223, miR-320, miR-486, miR-150, and miR-29b werelower in diabetic subjects, whereas miR-28-3p tended to behigher (Figure 2). Findings were consistent for expressionlevels standardized to either miR-454 or RNU6b (Figure 2)and for nonstandardized miRNA levels (data not shown).Nine miRNAs standardized to RNU6b showed significantdifferences between patients with DM and controls, and 4remained significant after accounting for the multiple com-

parisons performed (Bonferroni probability value�0.000133), including endothelial miR-126. Bonferroni cor-rection, however, is overly conservative in this setting be-cause individual miRNAs are not independent of each otherbut extensively correlated. In multivariate analyses, all miR-NAs except miR-29b were significantly associated withmanifest DM. Eleven showed an inverse relationship andmiR-28-3p a positive one. Findings for miRNAs standardizedto miR-454 are summarized in Figure 2 and were similar indiabetic patients with or without drug treatment (mainlysulfonylureas). In another run, miR-126 was quantified in theentire Bruneck cohort (n�822) and standardized againstmiR-454. In logistic regression analyses, miR-126 emergedagain as a significant predictor of manifest DM (odds ratio[95% confidence interval {CI}] for a 1-SD unit decrease ofloge-transformed expression level of miR-126, 2.23 [1.69 to2.96]; P�2.28�10�8), and this association persisted in amultivariable model (odds ratio [95% CI], 1.64 [1.19 to 2.28];P�0.0027). Moreover, there was a gradual decrease inplasma levels of miR-126 across categories of normal glucosetolerance (n�580), impaired fasting glucose/impaired glu-

Figure 2. Association of plasma miR-NAs with manifest DM. Thirteen plasmamiRNAs were quantified by qPCR inpatients with prevalent DM and matchedcontrols (n�80 each). Bars in the cen-ter of each graph represent foldchanges of plasma miRNA levelsbetween diabetic patients and controls.Bars on the left provide a comparison(fold changes) between plasma obtainedfrom hyperglycemic Lepob and controlmice. Squares and lines on the rightrepresent odds ratios (95% CIs) derivedfrom multivariable logistic regressionanalyses for matched data (human stud-ies). Probability values were from thenonparametric Wilcoxon test for relatedsamples (human studies, center) andMann–Whitney U test for unrelated sam-ples (animal studies), and from multivari-able logistic regression analyses formatched data (human studies).




cose tolerance (n�162) and manifest DM (n�80) (Figure 3).As expected, levels of miRNAs were inversely correlated withfasting glucose levels in both patients with DM, as well ascontrol subjects (r��0.191 to �0.335, P�0.05 each exceptmiR-29b and miR-320) and less consistently with 2-hour glu-cose levels (r��0.091 to �0.239) and HbA1c concentrations(r��0.093 to �0.312). Most of the miRNA changes observedin DM could independently be replicated in plasma samples of8 to 12 week old hyperglycemic Lepob mice (Figure 2).

Incident DMImportantly, several miRNAs were already altered beforemanifestation of DM. A total of 19 subjects, who werenormoglycemic in 1995, developed DM over the 10-yearfollow-up period (1995 to 2005 mean interval until diagnosisof DM 79.2 months). Baseline levels of miR-15a, miR-29b,miR-126, and miR-223 were significantly lower in thesesubjects, whereas miR-28-3p was higher compared tomatched controls (Figure 4).

MiRNAs as Biomarkers in DMTo determine whether miRNAs can correctly distinguishindividuals with prevalent or incident DM from healthy

controls, we reduced miRNA expression to principal compo-nents (PC). Interestingly, 91/99 (92%) controls and 56/80(70%) DM cases were correctly classified using expressionprofiles of 5 most significant miRNAs (miR-15a, miR-126,miR-320, miR-223, miR-28-3p) (Figure 5). The 24 DM casesthat were classified as normal subjects had significantly lowerlevels of fasting glucose (mean� SD, 120.0�28.6 mg/dLversus 147.2�55.0 mg/dL, P�0.005) and HbA1c (mean�SD, 6.03�0.75% versus 6.66�1.54%, P�0.016) and repre-sent a selection of patients with well-controlled DM. Impor-tantly, using this model 10/19 (52%) of normoglycemicsubjects that developed DM over the 10-year follow-upperiod were already classified as diabetics. Inclusion ofadditional miRNAs into the classification did not improvemodel performance (Figure 5B). Thus, these 5 miRNA can beconsidered as minimal requirement for classification using amiRNA signature. Further support to the putative value ofmiRNAs as diagnostic tools in DM was provided by theinference of miRNA relevance network (Online Figure III).

MiRNA-126 in DMAmong the miRNAs most consistently associated with DM wasmiR-126. This miRNA has previously been shown to be highlyenriched in endothelial cells and endothelial apoptotic bodiesand to govern the maintenance of vascular integrity, angiogen-esis, and wound repair.34–35 To determine whether hyperglyce-mia affects miR-126 release from endothelial cells, miRNAlevels of shedding endothelial particles (apoptotic bodies) andmicroparticles derived under normal (5 mmol/L) and high(25 mmol/L) glucose concentrations were compared. Whereascellular miRNA concentrations remained unaltered, high glu-cose significantly reduced the miR-126 content in endothelialapoptotic bodies (Figure 6A). Shedding of other miRNAs exceptmiR-24 was not affected (Online Figure IV). Consistent withthese in vitro experiments, the reduction in miR-126 levels inpatients with DM was confined to the particulate fraction inplasma (Figure 6B). Finally, evidence from our population

Figure 3. Plasma levels of miR-126 across categories of nor-mal glucose tolerance (NGT), impaired fasting glucose/im-paired glucose tolerance (IFG/IGT), and manifest DM.Squares and lines indicate adjusted geometric means and 95%CIs (white squares, values adjusted for age and sex; blacksquares, values adjusted for age, sex, social status, family his-tory of DM, body mass index, waist-to-hip ratio, smoking status,alcohol consumption (g/d), physical activity (sports index), andhigh-sensitivity C-reactive protein). This analysis was performedin the entire study population (n�822). Differences in miR-126between categories of NGT, IFG/IGT and DM were comparedwith General Linear Models and probability values are for trend.World Health Organization definition of categories: normal glu-cose tolerance (fasting glucose, �110 mg/dL; 2-hour glucose,�140 mg/dL), impaired fasting glucose/impaired glucose toler-ance (110 mg/dL�fasting glucose�126 mg/dL, 140 mg/dL�2-hour glucose�200 mg/dL) and manifest DM. American DiabetesAssociation definition of categories: normal glucose tolerance(fasting glucose, �100 mg/dL; 2-hour glucose, �140 mg/dL),impaired fasting glucose/impaired glucose tolerance (100mg/dL�fasting glucose�126 mg/dL, 140 mg/dL�2-hour glu-cose�200 mg/dL) and manifest DM.

Figure 4. Association of plasma miRNAs with incident DM.Thirteen plasma miRNAs were quantified by qPCR in patients whodeveloped DM over a 10-year observation period and matchedcontrols. Probability values were derived from the nonparametricWilcoxon test for related samples. *P�0.05, ***P�0.001.




cohort suggests that loss of miR-126 in plasma correlates withsubclinical and manifest peripheral artery disease. In detail,miR-126 was associated with a low ankle-brachial index (� 0.9,n�77) (unadjusted and age-/sex-adjusted odds ratio [95% CI]for a 1-SD unit decrease of loge-transformed expression level ofmiR-126, 1.95 [1.48 to 2.57], P�0.001; and 1.39 [1.04 to 1.86],P�0.025) and with new-onset symptomatic peripheral arterydisease (1995 to 2005, n�15) (unadjusted and age-/sex-adjustedhazard ratio [95% CI] for a 1-SD unit decrease of loge-transformed expression level of miR-126, 2.63 [1.38 to 5.02],P�0.0032; and 2.15 [1.06 to 4.38], P�0.030). In the latteranalysis, 37 subjects with symptomatic peripheral artery diseaseat baseline were excluded.

DiscussionWe provide the first evidence for a plasma miRNA signature inpatients with DM and a potential prognostic value in this setting.Our findings warrant further investigations into the role ofmiRNAs in diabetic vascular and myocardial complications.

Plasma MiRNAs in DMUsing differential expression and concepts of network topology,we identified 13 plasma miRNAs in DM including loss ofmiR-126. Findings were robust in multivariable analyses ofpatients with DM and age- and sex-matched controls andconfirmed in hyperglycemic Lepob mice. Of note, deregulationof several plasma miRNAs antedated the manifestation of DM.

Figure 5. Classification, PCA, and net-work properties. A, Classification effi-ciency of 13 miRNAs across control sub-jects (n�99), patients with incident DM(n�19), and manifest DM (n�80). Higherscore is indicative of a greater degree ofdifferential expression and thus a higherclassification potential. B, Classificationaccuracy. Best classification accuracywas achieved using the top 5 differen-tially expressed miRNAs. C, PCA, atechnique that reduces the data to twoor more uncorrelated principal compo-nents (PC) that explain most of the vari-ance, was used to determine whethercontrol subjects could be distinguishedfrom cohorts with incident and manifestDM. PCA decomposition of the top 5miRNAs was sufficient to clustertogether 91/99 (92%) controls and 56/80(70%) patients with manifest DM. Inter-estingly, 10/19 (52%) patients with inci-dent DM were clustered with cases ofmanifest disease.

Figure 6. The effect of increased glu-cose levels on the miR-126 content ofvesicles. High glucose concentrationsled to a decrease in the miR-126content of endothelial-derived particles(apoptotic bodies) (A) and circulatingvesicles in plasma (B). MiRNA expres-sion was assessed using qPCR. miR-454 was used as a normalization control.The data are from 4 independent experi-ments and presented as means�SD.*P�0.05.




Principal component analysis (PCA) of the 13 studied miRNAsindicates that 5 miRNAs (miR-15a, miR-126, miR-320, miR-223, miR-28-3p) with the highest scores are necessary andsufficient for a nonredundant classification. Although the func-tion of the highest scoring miRNA, miR-15a is unknown in DM,miR-15a has been previously implicated in cell cycle control andapoptosis in cancer cells.32 Its expression was shown to inverselycorrelate with the expression of cyclin D1, although it was alsoreported to negatively regulate levels of B-cell lymphoma 2(Bcl-2), a key antiapoptotic protein.33 In Lepob mice, however,miR-15a was not significantly different from wild-type mice,probably attributable to low plasma levels. Clinically relevantquestions are whether miRNA levels are capable of assessing theprobability of DM manifestation in high-risk individuals likepatients with impaired fasting glucose, borderline levels ofHbA1c or metabolic syndrome, and whether miRNAs can assistin the prediction of micro- and macrovascular complications inDM. Our data suggest that plasma miRNAs might be a usefulpredictive tool in DM but await confirmation in larger collec-tives of patients with DM and prediabetes before more definitivecomparisons with other standard risk factors can be made.MiR-126, however, deserves special consideration.

MiR-126 and DMPlasma levels of miR-126 were determined in the entire Bruneckcohort. This is, to our knowledge, the first time a miRNA hasbeen measured in a large population-based study. Whereas mostplasma miRNAs are ubiquitously expressed, miR-126 is highlyenriched in endothelial cells and plays a pivotal role in main-taining endothelial homeostasis and vascular integrity.35 It facil-itates vascular endothelial growth factor (VEGF) signaling byrepressing 2 negative regulators of the VEGF pathway, includ-ing the Sprouty-related protein SPRED1 and phosphoinositol-3kinase regulatory subunit 2 (PIK3R2/p85-�).34 Plasma miRNAsare packaged in membranous vesicles that change in numbers,cellular origin, and composition depending on the disease state.36

Accumulating evidence support the notion that these vesicles arenot just byproducts resulting from cell activation or apoptosis.Instead, they constitute a novel type of cell–cell mechanism ofcommunication. For example, miR-126 is the most abundantmiRNA in endothelial apoptotic bodies.37 Shedding of miR-126from endothelial cells has been shown to regulate VEGFresponsiveness and to confer vascular protection in a paracrinemanner.37 In our study, loss of miR-126 was consistentlyassociated with DM and the miR-126 content in endothelialapoptotic bodies was reduced in a glucose-dependent fashion.Because apoptotic bodies and microparticles can be transferredto other cell types,31,37 low plasma levels might result in reduceddelivery of miR-126 to monocytes and contribute to VEGFresistance and endothelial dysfunction. This view is corroboratedby previous reports that monocytes of patients with DM showimpaired responsiveness to VEGF contributing to defects incollateral vessel development38 and by our finding that loss ofmiR-126 confers an elevated risk of symptomatic and subclini-cal peripheral artery disease in the Bruneck population.

Potential Clinical ImplicationsThere are currently no good soluble biomarkers for atheroscle-rosis and/or endothelial dysfunction. Inflammatory markers such

as high-sensitivity C-reactive protein are widely used, but theylack specificity for the vasculature. Moreover, the existingimaging techniques mainly capture the endstage of the disease,eg, the occurrence of plaques, but not its earliest stage such asendothelial dysfunction. If certain plasma miRNAs wereuniquely modified by vascular injury, they may be capable ofadding to the predictive value of conventional risk factors.

Merits and LimitationsStrengths of our study are its considerable size, repre-sentativity for the general community, high methodologicalstandards, control for multiple testing, network analyses,rigorous replication using distinct techniques, various stan-dards (miR-454, RNU6b), and different systems (plasma, cellculture) and species (human, obese mice). As limitations, theparticulate fraction in plasma will contain other particlesbesides endothelial apoptotic bodies and the microarray usedfor the initial screening did not consider all miRNAs cur-rently known. Accordingly, we cannot claim completenessfor the miRNA profile among patients with DM and studiesin large collectives of patients with DM and prediabetes arerequired to assess the potential of the reported miRNAsignature and to establish miRNA–drug interactions.

ConclusionThis study provides the first evidence that plasma miRNAs,including endothelial miR-126, are deregulated in patientswith DM, which may ultimately lead to novel biomarkers forrisk estimation and classification39 and could be exploited formiRNA-based therapeutic interventions of vascular compli-cations associated with this disease.

Sources of FundingThis work was funded by the British Heart Foundation. M.M. is aSenior Research Fellow of the British Heart Foundation.

DisclosuresA.Z., S.K., I.D., J.W., and M.M. filed a patent application, owned byKing’s College London, that details claims related to describedcirculating miRNAs as biomarkers for DM.

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Novelty and Significance

What Is Known?

● MicroRNAs are small noncoding regulatory RNAs that alter proteinexpression.

● Some microRNAs circulate in plasma vesicles and have beenproposed as potential biomarkers for cancer, sepsis, myocardialinfarction and heart failure.

What New Information Does This Article Contribute?

● First evidence that plasma miRNAs are deregulated in patients withtype 2 diabetes.

● The distinct plasma miRNA pattern in diabetes includes loss ofmiR-126, a miRNA that is highly enriched in endothelial cells andfacilitates VEGF signaling.

● In a population-based study, miR-126 plasma levels negativelycorrelate with subclinical and manifest peripheral arterydisease.

Our study is the first to reveal a plasma miRNA signature in alarge population-based cohort of type 2 diabetics. We identifieda set of circulating miRNAs that display altered expression indiabetes and characterized dynamic changes in miRNA coex-pression networks. This may ultimately lead to novel biomarkersfor risk estimation and classification and could be exploited formiRNA-based therapeutic interventions of vascular complica-tions associated with this disease.




1

Supplemental Material

Plasma miRNA Profiling Reveals Loss of Endothelial MiR-126 and Other MiRNAs in Type II

Diabetes



2

Abbreviations

ABI: ankle-brachial index

CLR: Context likelihood of relatedness

DM: type II diabetes

GLM: General linear models

HUVEC: Human umbilical vein endothelial cells

Lepob: Leptin obese

MCL: Markov clustering

MiRNA: microRNA

MP: Microparticles

PCA: Principal component analysis

PCC: Pearson correlation coefficient

SVM: Support vector machines



3

Methods

Clinical history and examination. Smoking status was assessed in each subject 1-5. Regular

alcohol consumption was quantified in terms of grams per day. Hypertension was defined as blood

pressure (mean of 3 measurements) ≥ 140/90 mm Hg or the use of antihypertensive drugs. Body

mass index was calculated as weight divided by height squared (kg/m2). Waist and hip

circumferences (to the nearest 0.5 cm) were measured by a plastic tape meter at the level of the

umbilicus and of the greater trochanters, respectively, and waist-to-hip ratios (WHR) were

calculated. Socioeconomic status was assessed on a three-category scale (low, medium, high) based

on information about occupational status and educational level of the person with the highest

income in the household. Family history of DM refers to first-degree relatives. Physical activity was

quantified by the Baecke Score (index for sports activity) 6.

Laboratory methods. Blood samples were drawn after an overnight fast and 12 hours’ abstinence

from smoking 2-5. Plasma samples were aliquoted, stored at -80°C and thawed once before analysis.

A 75 g oral glucose load (oral glucose tolerance test, OGTT) was administered to all subjects

without known DM and blood samples were collected after 120 minutes in order to establish

glucose tolerance. High-density lipoprotein (HDL) cholesterol was determined enzymatically

(CHOD-PAP method, Merck; CV 2.2% to 2.4%). Low-density lipoprotein (LDL) cholesterol was

calculated with the Friedewald formula except in subjects with triglycerides >4.52 mmol/L in

whom it was directly measured. Markers of inflammation and all other laboratory parameters were

assessed by standard methods as detailed previously 1-5.

Obese mice. All animal experiments were performed according to protocols approved by the

Institutional Committee for Use and Care of Laboratory Animals. To determine whether miRNA

profiles identified in diabetic subjects also apply to hyperglycaemic animals7, we quantified plasma

levels in obese mice. For this purpose 8-12 week old female Lepob mice (previously known as

ob/ob) (n=6) were purchased from Jackson laboratories. C57BL/6J mice were used as a control

(n=6). A total of 1 ml of blood was harvested from each mouse and plasma was isolated following

centrifugation at 1,200g for 20 min at 4°C. Plasma samples were aliquoted and stored at -80°C.

RNA isolation from plasma. Total RNA was prepared using the miRNeasy kit (Qiagen) according

to the manufacturer’s recommendations. In brief, 200 µl of plasma was transferred to an Eppendorf

tube and mixed thoroughly with 700µl of QIAzol reagent. Following a brief incubation at ambient

temperature, 140 µl of chloroform were added and the solution was mixed vigorously. The samples



4

were then centrifuged at 12,000 rpm for 15 min at 4°C. The upper aqueous phase was carefully

transferred to a new tube and 1.5 volumes of ethanol were added. The samples were then applied

directly to columns and washed according to the company’s protocol. Total RNA was eluted in 25

µl of nuclease free H2O. A fixed volume of 3 µl of RNA solution from the 25 µl eluate was used as

input in each reverse transcription reaction.

RNA isolation from circulating vesicles. To isolate circulating vesicles, plasma samples from

diabetic or healthy subjects were pooled together (30 samples per pool) and three pools were

generated per group. Vesicles were isolated by ultracentrifugation. In brief, plasma samples were

centrifuged for 10 min at 800g to remove any precipitate and the particulate fraction including

apoptotic bodies was then isolated by centrifugation of the supernatant at 10,600 rpm for 20 min.

The pellet was resuspended in PBS. An additional centrifugation of the supernatant at 20,500 rpm

for 2h was performed to isolate microparticles. The pelleted microparticles were resuspended in

PBS and the remaining supernatant was considered as microvesicle-depleted plasma. Total RNA

was isolated using the miRNeasy kit as described above.

Reverse transcription and pre-amplification. To assess levels of specific miRNAs in individual

plasma samples a fixed volume of 3 µl of RNA solution from the 25 µl eluate was used as input in

each reverse transcription (RT) reaction. An RT reaction and pre-amplification step were set up

according to the company’s recommendations and performed as described above. RT-PCR and pre-

amplification products were stored at -20°C. miRNAs were reverse transcribed using the Megaplex

Primer Pools (Human Pools A v2.1 and B v2.0) from Applied Biosystems. Pool A enables

quantitation of 377 human miRNAs while an additional 290 miRNAs were assessed using Pool B.

In each array, three endogenous controls and a negative control were included for data

normalization. RT reaction was performed according to the company’s recommendations (0.8 µl of

Pooled Primers were combined with 0.2 µl of 100mmol/L dNTPs with dTTP, 0.8 µl of 10x

Reverse-Transcription Buffer, 0.9 µl of MgCl2 (25mmol/L), 1.5 µl of Multiscribe Reverse-

Transcriptase and 0.1 µl of RNAsin (20U/µl) to a final volume of 7.5 µl. The RT-PCR reaction was

set as follows: 16°C for 2 min, 42°C for 1 min and 50°C for 1 sec for 40 cycles and then incubation

at 85°C for 5 min using a Veriti thermocycler (Applied Biosystems). The RT reaction products

were further amplified using the Megaplex PreAmp Primers (Primers A v2.1 and B v2.0). A 2.5 µl

aliquot of the RT product was combined with 12.5 µl of Pre-amplification Mastermix (2x) and 2.5

µl of Megaplex PreAmp Primers (10x) to a final volume of 25 µl. The pre-amplification reaction

was performed by heating the samples at 95°C for 10 min, followed by 12 cycles of 95°C for 15 sec

and 60°C for 4 min. Finally, samples were heated at 95°C for 10 min to ensure enzyme inactivation.

Pre-amplification reaction products were diluted to a final volume of 100 µl and stored at -20°C.



5

Taqman miRNA array. The expression profile of miRNAs in plasma samples was determined

using the Human Taqman miRNA Arrays A and B (Applied Biosystems). PCR reactions were

performed using 450 µl of the Taqman Universal PCR Master Mix No AmpErase UNG (2x) and 9

µl of the diluted pre-amplification product to a final volume of 900 µl. 100µl of the PCR mix was

dispensed to each port of the Taqman miRNA Array. The fluidic card was then centrifuged and

mechanically sealed. QPCR was carried out on an Applied Biosystems 7900HT thermocycler using

the manufacturer’s recommended programme. Detailed analysis of the results was performed using

the Real-Time Statminer Software (Integromics).

Taqman qPCR assay. Taqman miRNA assays were used to assess the expression of individual

miRNAs. 0.5µl of the diluted pre-amplification product were combined with 0.25 µl of Taqman

miRNA Assay (20x) (Applied Biosystems) and 2.5 µl of the Taqman Universal PCR Master Mix

No AmpErase UNG (2x) to a final volume of 5 µl. QPCR was performed on an Applied Biosystems

7900HT thermocycler at 95°C for 10 min, followed by 40 cycles of 95°C for 15 sec and 60°C for 1

min. All samples were run in duplicates and standardized to miR-454 and RNU6b using SDS2.2

(Applied Biosystems) software. For sensitivity analyses, levels of miRNAs for PCR efficacy were

corrected using the LinRegPCR software.

Network clustering. Modular structure of the miRNA co-expression network was identified using

the Markov Clustering (MCL) algorithm 8. This is an efficient, unsupervised, and highly accurate

graph clustering approach based on graph flow simulation 9. A distinct advantage of MCL is its

ability to avoid incorrect clustering assignments in the presence of false negative edges. This is due

to the fact that MCL discovers clusters by virtue of miRNAs sharing higher-order connectivity in

their local neighborhood and not merely pair-wise linkages.

MiRNA feature selection, principal component analysis (PCA), and classification. Of the 30

differentially expressed miRNAs, 13 targets with extreme distributions in node degree, clustering

coefficient, and eigenvector centrality were selected for qPCR validation. Predictive significance of

validated miRNAs was calculated using bootstrap aggregation for an ensemble of 10,000 decision

trees. Each miRNA profile was assigned an importance value based on how well it can differentiate

control, incident DM, and manifest DM cases. The discriminatory power of the PCA was quantified

using the Support Vector Machines (SVM) algorithm, a supervised learning method. SVM were

trained on half of the data selected at random and validated on the remaining samples. This

procedure was repeated 10 times and the final correct classification rate was presented as an

average of all SVM iterations.



6

Ascertainment of peripheral artery disease. The ankle-brachial index (ABI) was measured in a

supine position. A cuff was inflated to 10 mmHg above systolic blood pressure and deflated at 2

mmHg/s. The first reappearance of the arterial signal at the ankle (posterior tibial artery) was taken

as the systolic blood pressure (detected with a Doppler ultrasonic instrument). To calculate the ABI

for the right and left leg, the systolic blood pressure at each ankle was divided by the systolic blood

pressure in the arm. The higher arm reading (right or left side) was used for ABI calculation. An

ABI < 0.9 was considered indicative of peripheral artery disease (low ABI). The diagnosis of new-

onset (1995-2005) symptomatic peripheral artery disease required (1) a positive response to the

Rose questionnaire (intermittent claudication) with the vascular nature of complaints confirmed by

standard diagnostic procedures (ankle-brachial pressure index, ultrasound or angiography) or (2) an

acute peripheral artery occlusion necessitating revascularization (angioplasty and surgery).

Ascertainment of events did not rely on hospital discharge codes or the patient’s self-report but on a

careful review of medical records provided by the general practitioners, death certificates, and

Bruneck Hospital files, and the extensive clinical and laboratory examinations performed as part of

the study protocols. Major advantages of the Bruneck Study are that virtually all subjects living in

the Bruneck area were referred to the local hospital and that the network existing between the local

hospital and the general practitioners allowed retrieval of practically all medical information on

persons living in the area.



7

References 1. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Meigs JB, Bonadonna RC,

Muggeo M. Population-based incidence rates and risk factors for type 2 diabetes in white individuals: the Bruneck study. Diabetes. 2004;53:1782-1789.

2. Tsimikas S, Willeit J, Knoflach M, Mayr M, Egger G, Notdurfter M, Witztum JL, Wiedermann CJ, Xu Q, Kiechl S. Lipoprotein-associated phospholipase A2 activity, ferritin levels, metabolic syndrome, and 10-year cardiovascular and non-cardiovascular mortality: results from the Bruneck study. Eur Heart J. 2009;30:107-115.

3. Kiechl S, Lorenz E, Reindl M, Wiedermann CJ, Oberhollenzer F, Bonora E, Willeit J, Schwartz DA. Toll-like receptor 4 polymorphisms and atherogenesis. N Engl J Med. 2002;347:185-192.

4. Kiechl S, Schett G, Schwaiger J, Seppi K, Eder P, Egger G, Santer P, Mayr A, Xu Q, Willeit J. Soluble receptor activator of nuclear factor-kappa B ligand and risk for cardiovascular disease. Circulation. 2007;116:385-391.

5. Kiechl S, Willeit J, Mayr M, Viehweider B, Oberhollenzer M, Kronenberg F, Wiedermann CJ, Oberthaler S, Xu Q, Witztum JL, Tsimikas S. Oxidized phospholipids, lipoprotein(a), lipoprotein-associated phospholipase A2 activity, and 10-year cardiovascular outcomes: prospective results from the Bruneck study. Arterioscler Thromb Vasc Biol. 2007;27:1788-1795.

6. Baecke JA, Burema J, Frijters JE. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr. 1982;36:936-942.

7. Coleman DL. Obese and diabetes: two mutant genes causing diabetes-obesity syndromes in mice. Diabetologia. 1978;14:141-148.

8. van Dongen S. Graph clustering by flow simulation [PhD], University of Utrecht; 2000. 9. Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection

of protein families. Nucleic Acids Res. 2002;30:1575-1584.



8

Online Table I. Characteristics of patients with manifest DM and age-/sex-matched controls (Bruneck Study).

Characteristic*

DM (n=80) Control (n=80)

Demographic variables

Age, years

66.3±8.9 66.3±8.9

Female sex, n (%) 50 (62.5) 50 (62.5)

Social status, n (%)

Low 60 (75.0) 51 (63.8)

Middle 10 (12.5) 15 (18.8)

High 10 (12.5) 14 (17.5)

Lifestyle and diabetes risk factors

Smoking, n (%) 9 (11.3) 10 (12.5)

Family history of diabetes, n (%) 26 (32.5) 17 (21.3)

Alcohol consumption, grams/day 18.6±28.9 18.4±25.0

Physical activity (sport index) 1.7±0.9 2.2±0.8

Body mass index, kg/m² 28.0±4.4 25.0±4.0

Waist-to-hip ratio, cm/cm 0.95±0.07 0.92±0.08

Hypertension, n (%) 71 (88.8) 58 (72.5)

HDL cholesterol, mg/dL 53.9±13.7 62.7±19.5

LDL cholesterol, mg/dL 146.2±39.1 140.4±35.2

Triglycerides, mg/dL 141[99-186] 91[73-125]

High-sensitivity CRP, mg/L 3.0[1.6-6.5] 1.9[0.9-3.0]

Glycaemia

Fasting glucose, mg/dL 139.0±50.0 91.6±5.9

2-hr glucose, mg/dL 232.6±81.6 94.1±21.5

Glycated hemoglobin (Hba1c), % 6.5±1.4 5.4±0.3

* Values presented are unadjusted means ± SD, medians [IQR] or numbers (percentages).



9

Online Table II. Circulating miRNAs and differentially expressed miRNAs in DM.

Identified Targets Ct values (cycles)

miR-17, miR-92a, miR-106a, miR-146a, miR-150, miR-191, miR-223, miR-320, miR-484

22-25

miR-16, miR-19b, miR-20a, miR-20b, miR-24, miR-28-3p, miR-29b, miR-30b, miR-30c, miR-106b, miR-126, miR-197, miR-222, miR-331, miR-342-3p, miR-483-5p

25-28

let-7e, miR-10a, miR-21, miR-29a, miR-93, miR-106b, miR-133, miR-139-5p, miR-145, miR-146b-5p, miR-185, miR-186, miR-199a, miR-328, miR-425, miR-486-3p, miR-495, miR-574-3p

28-30

let-7f, let-7b, miR-15a, miR-19a, miR-25, miR-26a, miR-27a, miR-28-5p, miR-99b, miR-100, miR-103, miR-122, miR-125-5p, miR-127-3p, miR-134, miR-139-3p, miR-140-5p, miR-142-3p, miR-152, miR-193-5p, miR-204, miR-221, miR-224, miR-339-3p, miR-345, miR-375, miR-376a, miR-423-5p, miR-433, miR-454, miR-486-5p, miR-491-5p, miR-517a, miR-532-3p, miR-539, miR-744, miR-885-5p, miR-886-3p,

30-32

let-7c, let-7f, let-7g, miR-1, miR-9, miR-10b, miR-15b, miR-23a, miR-28-5p, miR-32, miR-101, miR-129-3p, miR-138, miR-140, miR-143,miR-148a, miR-181a, miR-192, miR-193a-3p, miR-193b, miR-195, miR-198, miR-204, miR-301a, miR-324, miR-330-3p, miR-331, miR-335, miR-361-5p, miR-365, miR-374a, miR-374b, miR-411, miR-451, miR-486-3p, miR- 494, miR-502-3p, miR-519e, miR-520d-5p, miR-532-3p, miR-532-5p, miR-548a-3p, miR-590-5p, miR-598, miR-625, miR-629, miR-636, miR-652, miR-660, miR-886-5p, miR-376c, miR-30e*, miR-505*, miR-130b*, miR-93*, miR-99b*, miR-541*, miR-425*, miR-19b-1*, miR-643, miR-610, miR-520c, miR-513-3p, miR-509-3p, miR-30a, miR-572, miR-571

32-35

Bold font highlights differentially expressed miRNAs in DM



10

Online Table III. miRNA-miRNA co-expression network

Node A Node B PCC let-7b let-7d 0.86 let-7c miR-100 0.86 let-7d miR-106b 0.86 miR-103 miR-106b 0.99 miR-106a miR-106b 0.85 let-7d miR-122 0.87 miR-106a miR-126 0.97 miR-103 miR-127-3p 0.90 miR-106a miR-127-3p 0.91 miR-106b miR-127-3p 0.90 miR-126 miR-127-3p 0.85 miR-1 miR-129-3p 0.91 let-7e miR-133a 0.90 miR-103 miR-133a 0.85 miR-106a miR-133a 0.87 miR-106b miR-133a 0.87 miR-126 miR-133a 0.88 miR-127-3p miR-133a 0.89 miR-101 miR-138 0.91 miR-103 miR-139-3p 0.86 miR-106a miR-139-3p 0.90 miR-127-3p miR-139-3p 0.95 let-7d miR-139-5p 0.86 miR-106a miR-139-5p 0.94 miR-122 miR-139-5p 0.88 miR-126 miR-139-5p 0.92 miR-127-3p miR-139-5p 0.87 miR-103 miR-140-3p 0.88 miR-139-3p miR-140-3p 0.89 let-7e miR-140-5p 0.88 miR-106a miR-140-5p 0.88 miR-126 miR-140-5p 0.87 miR-127-3p miR-140-5p 0.88 miR-133a miR-140-5p 0.93 miR-139-3p miR-140-5p 0.88 let-7e miR-142-3p 0.88 let-7e miR-145 0.86 miR-103 miR-145 0.90 miR-106a miR-145 0.89 miR-106b miR-145 0.89 miR-126 miR-145 0.89 miR-127-3p miR-145 0.92 miR-133a miR-145 0.96 miR-139-3p miR-145 0.91 miR-140-5p miR-145 0.96 miR-142-3p miR-145 0.85 miR-106a miR-146a 0.91 miR-126 miR-146a 0.94 miR-140-5p miR-146a 0.85



11

miR-143 miR-146a 0.88 miR-103 miR-148a 0.88 miR-140-3p miR-148a 0.86 miR-126 miR-150 0.91 miR-146a miR-150 0.93 miR-146b-5p miR-150 0.96 let-7c miR-15a 0.89 miR-103 miR-15b 0.94 miR-106a miR-15b 0.88 miR-106b miR-15b 0.92 miR-126 miR-15b 0.86 miR-139-3p miR-15b 0.86 miR-145 miR-15b 0.89 miR-146a miR-15b 0.86 miR-106a miR-16 0.87 miR-126 miR-16 0.89 miR-146a miR-16 0.93 miR-15b miR-16 0.93 let-7e miR-17 0.90 miR-103 miR-17 0.88 miR-106a miR-17 0.92 miR-106b miR-17 0.88 miR-126 miR-17 0.93 miR-127-3p miR-17 0.87 miR-133a miR-17 0.94 miR-139-3p miR-17 0.86 miR-140-5p miR-17 0.95 miR-142-3p miR-17 0.87 miR-145 miR-17 0.98 miR-146a miR-17 0.91 miR-15b miR-17 0.92 miR-16 miR-17 0.87 let-7e miR-181a 0.90 miR-133a miR-181a 0.87 miR-140-5p miR-181a 0.97 miR-145 miR-181a 0.91 miR-17 miR-181a 0.90 let-7e miR-185 0.89 miR-133a miR-185 0.86 miR-142-3p miR-185 0.98 miR-145 miR-185 0.87 miR-17 miR-185 0.90 miR-126 miR-186 0.89 miR-133a miR-186 0.85 miR-140-5p miR-186 0.88 miR-142-3p miR-186 0.86 miR-145 miR-186 0.94 miR-146a miR-186 0.92 miR-15b miR-186 0.92 miR-16 miR-186 0.93 miR-17 miR-186 0.96 miR-181a miR-186 0.85



12

miR-185 miR-186 0.88 miR-143 miR-191 0.89 let-7d miR-192 0.85 miR-103 miR-192 0.98 miR-106a miR-192 0.90 miR-106b miR-192 0.99 miR-126 miR-192 0.87 miR-127-3p miR-192 0.91 miR-133a miR-192 0.89 miR-139-3p miR-192 0.86 miR-139-5p miR-192 0.88 miR-145 miR-192 0.92 miR-15b miR-192 0.96 miR-17 miR-192 0.93 miR-186 miR-192 0.87 miR-103 miR-193a-5p 0.94 miR-106b miR-193a-5p 0.93 miR-133a miR-193a-5p 0.86 miR-142-3p miR-193a-5p 0.90 miR-145 miR-193a-5p 0.92 miR-15b miR-193a-5p 0.94 miR-17 miR-193a-5p 0.94 miR-185 miR-193a-5p 0.94 miR-186 miR-193a-5p 0.91 miR-192 miR-193a-5p 0.95 let-7d miR-193b 0.86 miR-103 miR-193b 0.91 miR-106a miR-193b 0.96 miR-106b miR-193b 0.94 miR-126 miR-193b 0.94 miR-127-3p miR-193b 0.94 miR-133a miR-193b 0.88 miR-139-3p miR-193b 0.87 miR-139-5p miR-193b 0.95 miR-140-5p miR-193b 0.87 miR-145 miR-193b 0.92 miR-15b miR-193b 0.91 miR-16 miR-193b 0.88 miR-17 miR-193b 0.94 miR-186 miR-193b 0.86 miR-192 miR-193b 0.96 miR-193a-5p miR-193b 0.88 miR-181a miR-195 0.88 let-7e miR-197 0.85 miR-103 miR-197 0.90 miR-106a miR-197 0.93 miR-106b miR-197 0.91 miR-126 miR-197 0.95 miR-127-3p miR-197 0.87 miR-133a miR-197 0.92 miR-139-3p miR-197 0.86 miR-139-5p miR-197 0.86



13

miR-140-5p miR-197 0.90 miR-145 miR-197 0.96 miR-146a miR-197 0.91 miR-15b miR-197 0.96 miR-16 miR-197 0.91 miR-17 miR-197 0.98 miR-185 miR-197 0.89 miR-186 miR-197 0.96 miR-192 miR-197 0.95 miR-193a-5p miR-197 0.94 miR-193b miR-197 0.94 miR-138 miR-198 0.89 miR-133a miR-199a-3p 0.86 miR-140-3p miR-199a-3p 0.85 miR-140-5p miR-199a-3p 0.93 miR-145 miR-199a-3p 0.86 miR-181a miR-199a-3p 0.91 miR-133a miR-19a 0.87 miR-140-5p miR-19a 0.87 miR-142-3p miR-19a 0.92 miR-145 miR-19a 0.94 miR-146a miR-19a 0.87 miR-15b miR-19a 0.90 miR-16 miR-19a 0.87 miR-17 miR-19a 0.95 miR-181a miR-19a 0.85 miR-185 miR-19a 0.93 miR-186 miR-19a 0.99 miR-192 miR-19a 0.86 miR-193a-5p miR-19a 0.92 miR-197 miR-19a 0.95 let-7d miR-19b 0.86 miR-103 miR-19b 0.88 miR-106a miR-19b 0.94 miR-106b miR-19b 0.91 miR-126 miR-19b 0.96 miR-127-3p miR-19b 0.87 miR-133a miR-19b 0.89 miR-139-5p miR-19b 0.92 miR-145 miR-19b 0.92 miR-146a miR-19b 0.89 miR-15b miR-19b 0.95 miR-16 miR-19b 0.91 miR-17 miR-19b 0.95 miR-186 miR-19b 0.93 miR-192 miR-19b 0.95 miR-193a-5p miR-19b 0.90 miR-193b miR-19b 0.95 miR-197 miR-19b 0.99 miR-19a miR-19b 0.91 let-7d miR-204 0.87 miR-103 miR-204 0.88



14

miR-106a miR-204 0.93 miR-106b miR-204 0.91 miR-122 miR-204 0.86 miR-126 miR-204 0.95 miR-127-3p miR-204 0.87 miR-133a miR-204 0.87 miR-139-5p miR-204 0.93 miR-145 miR-204 0.90 miR-146a miR-204 0.88 miR-15b miR-204 0.95 miR-16 miR-204 0.92 miR-17 miR-204 0.93 miR-186 miR-204 0.91 miR-192 miR-204 0.96 miR-193a-5p miR-204 0.89 miR-193b miR-204 0.95 miR-197 miR-204 0.98 miR-19a miR-204 0.89 miR-19b miR-204 1.00 let-7d miR-20a 0.89 miR-103 miR-20a 0.90 miR-106b miR-20a 0.94 miR-122 miR-20a 0.88 miR-127-3p miR-20a 0.90 miR-133a miR-20a 0.88 miR-139-5p miR-20a 0.89 miR-145 miR-20a 0.85 miR-15b miR-20a 0.85 miR-192 miR-20a 0.94 miR-193b miR-20a 0.91 miR-197 miR-20a 0.88 miR-19b miR-20a 0.92 miR-204 miR-20a 0.92 miR-106a miR-20b 0.92 miR-106b miR-20b 0.87 miR-122 miR-20b 0.87 miR-126 miR-20b 0.88 miR-127-3p miR-20b 0.88 miR-139-5p miR-20b 0.94 miR-192 miR-20b 0.89 miR-193b miR-20b 0.90 miR-19b miR-20b 0.90 miR-204 miR-20b 0.90 miR-20a miR-20b 0.93 miR-103 miR-21 0.89 miR-106a miR-21 0.95 miR-106b miR-21 0.91 miR-126 miR-21 0.92 miR-127-3p miR-21 0.98 miR-133a miR-21 0.93 miR-139-3p miR-21 0.92 miR-139-5p miR-21 0.92



15

miR-140-5p miR-21 0.87 miR-145 miR-21 0.93 miR-15b miR-21 0.87 miR-17 miR-21 0.90 miR-192 miR-21 0.93 miR-193b miR-21 0.96 miR-197 miR-21 0.92 miR-19b miR-21 0.93 miR-204 miR-21 0.93 miR-20a miR-21 0.94 miR-20b miR-21 0.94 miR-103 miR-221 0.93 miR-106b miR-221 0.92 miR-148a miR-221 0.94 miR-192 miR-221 0.87 miR-193a-5p miR-221 0.86 let-7e miR-222 0.87 miR-106a miR-222 0.91 miR-126 miR-222 0.93 miR-140-5p miR-222 0.94 miR-145 miR-222 0.87 miR-146a miR-222 0.93 miR-150 miR-222 0.89 miR-17 miR-222 0.91 miR-181a miR-222 0.92 miR-186 miR-222 0.85 miR-191 miR-222 0.85 miR-197 miR-222 0.87 let-7e miR-223 0.90 miR-103 miR-223 0.86 miR-106a miR-223 0.95 miR-106b miR-223 0.88 miR-126 miR-223 0.96 miR-127-3p miR-223 0.92 miR-133a miR-223 0.95 miR-139-3p miR-223 0.87 miR-139-5p miR-223 0.88 miR-140-5p miR-223 0.95 miR-145 miR-223 0.97 miR-146a miR-223 0.88 miR-15b miR-223 0.88 miR-16 miR-223 0.86 miR-17 miR-223 0.98 miR-181a miR-223 0.90 miR-186 miR-223 0.92 miR-192 miR-223 0.92 miR-193a-5p miR-223 0.88 miR-193b miR-223 0.97 miR-197 miR-223 0.97 miR-19a miR-223 0.91 miR-19b miR-223 0.95 miR-204 miR-223 0.94



16

miR-20a miR-223 0.87 miR-21 miR-223 0.95 miR-222 miR-223 0.92 miR-103 miR-24 0.88 miR-106a miR-24 0.97 miR-106b miR-24 0.90 miR-126 miR-24 0.97 miR-127-3p miR-24 0.92 miR-133a miR-24 0.91 miR-139-3p miR-24 0.89 miR-139-5p miR-24 0.92 miR-140-5p miR-24 0.91 miR-145 miR-24 0.95 miR-146a miR-24 0.92 miR-15b miR-24 0.93 miR-16 miR-24 0.92 miR-17 miR-24 0.97 miR-186 miR-24 0.93 miR-192 miR-24 0.94 miR-193a-5p miR-24 0.89 miR-193b miR-24 0.98 miR-197 miR-24 0.98 miR-19a miR-24 0.90 miR-19b miR-24 0.98 miR-204 miR-24 0.97 miR-20a miR-24 0.88 miR-20b miR-24 0.88 miR-21 miR-24 0.95 miR-222 miR-24 0.90 miR-223 miR-24 0.99 miR-106a miR-25 0.96 miR-126 miR-25 0.91 miR-127-3p miR-25 0.97 miR-139-3p miR-25 0.94 miR-139-5p miR-25 0.90 miR-140-5p miR-25 0.90 miR-145 miR-25 0.90 miR-17 miR-25 0.88 miR-192 miR-25 0.86 miR-193b miR-25 0.94 miR-197 miR-25 0.87 miR-19b miR-25 0.86 miR-204 miR-25 0.86 miR-20b miR-25 0.86 miR-21 miR-25 0.96 miR-222 miR-25 0.87 miR-223 miR-25 0.93 miR-24 miR-25 0.94 miR-122 miR-26a 0.94 miR-125a-5p miR-26a 0.90 miR-139-5p miR-26a 0.94 miR-193b miR-26a 0.85



17

miR-204 miR-26a 0.86 miR-20a miR-26a 0.89 miR-20b miR-26a 0.96 miR-21 miR-26a 0.87 miR-106a miR-28-3p 0.90 miR-126 miR-28-3p 0.87 miR-127-3p miR-28-3p 0.91 miR-139-3p miR-28-3p 0.93 miR-140-5p miR-28-3p 0.96 miR-145 miR-28-3p 0.92 miR-146a miR-28-3p 0.87 miR-17 miR-28-3p 0.90 miR-181a miR-28-3p 0.90 miR-186 miR-28-3p 0.86 miR-193b miR-28-3p 0.88 miR-195 miR-28-3p 0.90 miR-197 miR-28-3p 0.86 miR-21 miR-28-3p 0.89 miR-222 miR-28-3p 0.92 miR-223 miR-28-3p 0.93 miR-24 miR-28-3p 0.91 miR-25 miR-28-3p 0.96 miR-106a miR-28-5p 0.90 miR-126 miR-28-5p 0.87 miR-129-3p miR-28-5p 0.88 miR-146b-5p miR-28-5p 0.85 miR-150 miR-28-5p 0.85 miR-222 miR-28-5p 0.90 miR-146b-5p miR-29b 0.97 miR-150 miR-29b 0.94 miR-191 miR-29c 0.92 let-7e miR-301a 0.86 let-7d miR-30b 0.86 let-7e miR-30b 0.93 miR-106a miR-30b 0.89 miR-106b miR-30b 0.87 miR-126 miR-30b 0.93 miR-127-3p miR-30b 0.88 miR-133a miR-30b 0.95 miR-139-5p miR-30b 0.85 miR-140-5p miR-30b 0.92 miR-142-3p miR-30b 0.89 miR-145 miR-30b 0.95 miR-17 miR-30b 0.97 miR-181a miR-30b 0.89 miR-185 miR-30b 0.88 miR-186 miR-30b 0.92 miR-192 miR-30b 0.91 miR-193a-5p miR-30b 0.89 miR-193b miR-30b 0.94 miR-197 miR-30b 0.95 miR-19a miR-30b 0.92



18

miR-19b miR-30b 0.94 miR-204 miR-30b 0.93 miR-20a miR-30b 0.89 miR-21 miR-30b 0.92 miR-222 miR-30b 0.87 miR-223 miR-30b 0.98 miR-24 miR-30b 0.96 miR-25 miR-30b 0.86 miR-28-3p miR-30b 0.86 let-7e miR-30c 0.86 miR-103 miR-30c 0.86 miR-106a miR-30c 0.92 miR-106b miR-30c 0.87 miR-126 miR-30c 0.95 miR-127-3p miR-30c 0.88 miR-133a miR-30c 0.95 miR-139-3p miR-30c 0.86 miR-140-5p miR-30c 0.91 miR-142-3p miR-30c 0.85 miR-145 miR-30c 0.97 miR-146a miR-30c 0.90 miR-15b miR-30c 0.92 miR-16 miR-30c 0.88 miR-17 miR-30c 0.98 miR-185 miR-30c 0.89 miR-186 miR-30c 0.96 miR-192 miR-30c 0.92 miR-193a-5p miR-30c 0.90 miR-193b miR-30c 0.92 miR-197 miR-30c 0.99 miR-19a miR-30c 0.96 miR-19b miR-30c 0.97 miR-204 miR-30c 0.96 miR-20a miR-30c 0.88 miR-21 miR-30c 0.93 miR-222 miR-30c 0.88 miR-223 miR-30c 0.97 miR-24 miR-30c 0.97 miR-25 miR-30c 0.86 miR-28-3p miR-30c 0.87 miR-30b miR-30c 0.96 miR-106a miR-320 0.90 miR-126 miR-320 0.94 miR-140-5p miR-320 0.89 miR-143 miR-320 0.89 miR-146a miR-320 0.98 miR-150 miR-320 0.94 miR-16 miR-320 0.87 miR-17 miR-320 0.90 miR-181a miR-320 0.85 miR-186 miR-320 0.89 miR-191 miR-320 0.86



19

miR-197 miR-320 0.88 miR-19b miR-320 0.86 miR-222 miR-320 0.98 miR-223 miR-320 0.89 miR-24 miR-320 0.91 miR-28-3p miR-320 0.90 miR-28-5p miR-320 0.87 miR-30c miR-320 0.88 miR-139-3p miR-323-3p 0.86 miR-25 miR-323-3p 0.85 miR-103 miR-324-3p 0.95 miR-106a miR-324-3p 0.91 miR-106b miR-324-3p 0.96 miR-126 miR-324-3p 0.90 miR-127-3p miR-324-3p 0.89 miR-133a miR-324-3p 0.89 miR-139-3p miR-324-3p 0.88 miR-139-5p miR-324-3p 0.87 miR-145 miR-324-3p 0.93 miR-15b miR-324-3p 0.98 miR-16 miR-324-3p 0.88 miR-17 miR-324-3p 0.94 miR-186 miR-324-3p 0.90 miR-192 miR-324-3p 0.99 miR-193a-5p miR-324-3p 0.94 miR-193b miR-324-3p 0.94 miR-197 miR-324-3p 0.98 miR-19a miR-324-3p 0.89 miR-19b miR-324-3p 0.98 miR-204 miR-324-3p 0.98 miR-20a miR-324-3p 0.92 miR-20b miR-324-3p 0.90 miR-21 miR-324-3p 0.93 miR-223 miR-324-3p 0.92 miR-24 miR-324-3p 0.95 miR-25 miR-324-3p 0.85 miR-30b miR-324-3p 0.90 miR-30c miR-324-3p 0.95 let-7e miR-328 0.86 miR-106a miR-328 0.87 miR-126 miR-328 0.87 miR-127-3p miR-328 0.91 miR-133a miR-328 0.94 miR-139-3p miR-328 0.89 miR-140-5p miR-328 0.99 miR-145 miR-328 0.98 miR-17 miR-328 0.96 miR-181a miR-328 0.96 miR-186 miR-328 0.92 miR-192 miR-328 0.86 miR-193a-5p miR-328 0.86 miR-193b miR-328 0.90



20

miR-195 miR-328 0.86 miR-197 miR-328 0.92 miR-199a-3p miR-328 0.89 miR-19a miR-328 0.91 miR-19b miR-328 0.86 miR-21 miR-328 0.90 miR-222 miR-328 0.90 miR-223 miR-328 0.97 miR-24 miR-328 0.93 miR-25 miR-328 0.91 miR-28-3p miR-328 0.96 miR-30b miR-328 0.94 miR-30c miR-328 0.93 miR-320 miR-328 0.86 miR-324-3p miR-328 0.86 miR-129-3p miR-330-3p 0.89 miR-146a miR-330-3p 0.91 miR-222 miR-330-3p 0.87 miR-28-5p miR-330-3p 0.90 miR-320 miR-330-3p 0.90 let-7e miR-331-3p 0.92 miR-103 miR-331-3p 0.86 miR-106a miR-331-3p 0.89 miR-106b miR-331-3p 0.88 miR-126 miR-331-3p 0.92 miR-133a miR-331-3p 0.97 miR-140-5p miR-331-3p 0.91 miR-142-3p miR-331-3p 0.89 miR-145 miR-331-3p 0.96 miR-146a miR-331-3p 0.86 miR-15b miR-331-3p 0.88 miR-17 miR-331-3p 0.98 miR-181a miR-331-3p 0.86 miR-185 miR-331-3p 0.93 miR-186 miR-331-3p 0.93 miR-192 miR-331-3p 0.92 miR-193a-5p miR-331-3p 0.93 miR-193b miR-331-3p 0.90 miR-197 miR-331-3p 0.97 miR-19a miR-331-3p 0.94 miR-19b miR-331-3p 0.95 miR-204 miR-331-3p 0.93 miR-20a miR-331-3p 0.86 miR-21 miR-331-3p 0.89 miR-222 miR-331-3p 0.87 miR-223 miR-331-3p 0.96 miR-24 miR-331-3p 0.95 miR-30b miR-331-3p 0.96 miR-30c miR-331-3p 0.98 miR-320 miR-331-3p 0.85 miR-324-3p miR-331-3p 0.94 miR-328 miR-331-3p 0.92



21

miR-101 miR-331-5p 0.99 miR-138 miR-331-5p 0.90 miR-198 miR-331-5p 0.87 miR-106a miR-342-3p 0.93 miR-126 miR-342-3p 0.96 miR-139-5p miR-342-3p 0.89 miR-146a miR-342-3p 0.92 miR-146b-5p miR-342-3p 0.92 miR-150 miR-342-3p 0.97 miR-193b miR-342-3p 0.86 miR-19b miR-342-3p 0.87 miR-204 miR-342-3p 0.86 miR-222 miR-342-3p 0.93 miR-223 miR-342-3p 0.88 miR-24 miR-342-3p 0.90 miR-28-5p miR-342-3p 0.91 miR-29b miR-342-3p 0.92 miR-320 miR-342-3p 0.94 let-7e miR-345 0.87 miR-142-3p miR-345 0.94 miR-17 miR-345 0.89 miR-185 miR-345 0.96 miR-186 miR-345 0.90 miR-193a-5p miR-345 0.92 miR-197 miR-345 0.86 miR-19a miR-345 0.93 miR-331-3p miR-345 0.88 miR-335 miR-361-5p 1.00 miR-301a miR-365 0.99 miR-103 miR-370 0.92 miR-106b miR-370 0.87 miR-140-3p miR-370 0.92 miR-145 miR-370 0.86 miR-148a miR-370 0.97 miR-15b miR-370 0.87 miR-192 miR-370 0.87 miR-193a-5p miR-370 0.88 miR-221 miR-370 0.90 miR-328 miR-370 0.85 let-7d miR-374a 0.86 miR-122 miR-374a 0.90 miR-20b miR-374a 0.85 miR-26a miR-374a 0.88 miR-339-3p miR-374a 0.85 miR-103 miR-374b 0.91 miR-106b miR-374b 0.86 miR-140-3p miR-374b 0.89 miR-148a miR-374b 0.97 miR-15b miR-374b 0.86 miR-193a-5p miR-374b 0.87 miR-221 miR-374b 0.90 miR-370 miR-374b 0.96



22

let-7d miR-375 0.88 miR-103 miR-375 0.93 miR-106a miR-375 0.87 miR-106b miR-375 0.96 miR-122 miR-375 0.88 miR-126 miR-375 0.86 miR-127-3p miR-375 0.91 miR-133a miR-375 0.87 miR-139-5p miR-375 0.90 miR-145 miR-375 0.89 miR-15b miR-375 0.93 miR-17 miR-375 0.89 miR-186 miR-375 0.85 miR-192 miR-375 0.97 miR-193a-5p miR-375 0.89 miR-193b miR-375 0.94 miR-197 miR-375 0.93 miR-19b miR-375 0.95 miR-204 miR-375 0.96 miR-20a miR-375 0.98 miR-20b miR-375 0.90 miR-21 miR-375 0.94 miR-223 miR-375 0.90 miR-24 miR-375 0.92 miR-26a miR-375 0.87 miR-30b miR-375 0.91 miR-30c miR-375 0.92 miR-324-3p miR-375 0.96 miR-331-3p miR-375 0.89 miR-106a miR-376a 0.87 miR-127-3p miR-376a 0.94 miR-139-3p miR-376a 0.91 miR-140-3p miR-376a 0.89 miR-140-5p miR-376a 0.89 miR-145 miR-376a 0.86 miR-193b miR-376a 0.88 miR-199a-3p miR-376a 0.88 miR-21 miR-376a 0.89 miR-223 miR-376a 0.86 miR-25 miR-376a 0.95 miR-28-3p miR-376a 0.91 miR-328 miR-376a 0.88 miR-191 miR-411 0.87 miR-103 miR-423-5p 0.90 miR-106b miR-423-5p 0.89 miR-127-3p miR-423-5p 0.89 miR-133a miR-423-5p 0.92 miR-139-3p miR-423-5p 0.86 miR-140-5p miR-423-5p 0.93 miR-142-3p miR-423-5p 0.90 miR-145 miR-423-5p 0.98 miR-15b miR-423-5p 0.90



23

miR-17 miR-423-5p 0.96 miR-181a miR-423-5p 0.89 miR-185 miR-423-5p 0.89 miR-186 miR-423-5p 0.95 miR-192 miR-423-5p 0.91 miR-193a-5p miR-423-5p 0.93 miR-193b miR-423-5p 0.89 miR-197 miR-423-5p 0.94 miR-19a miR-423-5p 0.96 miR-19b miR-423-5p 0.89 miR-204 miR-423-5p 0.88 miR-21 miR-423-5p 0.89 miR-223 miR-423-5p 0.94 miR-24 miR-423-5p 0.92 miR-28-3p miR-423-5p 0.88 miR-30b miR-423-5p 0.94 miR-30c miR-423-5p 0.95 miR-324-3p miR-423-5p 0.91 miR-328 miR-423-5p 0.97 miR-331-3p miR-423-5p 0.93 miR-345 miR-423-5p 0.86 miR-370 miR-423-5p 0.89 miR-375 miR-423-5p 0.90 miR-106a miR-425 0.99 miR-106b miR-425 0.88 miR-126 miR-425 0.97 miR-127-3p miR-425 0.93 miR-133a miR-425 0.87 miR-139-3p miR-425 0.89 miR-139-5p miR-425 0.96 miR-140-5p miR-425 0.86 miR-145 miR-425 0.90 miR-146a miR-425 0.89 miR-15b miR-425 0.90 miR-16 miR-425 0.89 miR-17 miR-425 0.91 miR-186 miR-425 0.85 miR-192 miR-425 0.92 miR-193b miR-425 0.98 miR-197 miR-425 0.94 miR-19b miR-425 0.96 miR-204 miR-425 0.96 miR-20a miR-425 0.88 miR-20b miR-425 0.93 miR-21 miR-425 0.97 miR-222 miR-425 0.88 miR-223 miR-425 0.95 miR-24 miR-425 0.98 miR-25 miR-425 0.96 miR-26a miR-425 0.88 miR-28-3p miR-425 0.89 miR-28-5p miR-425 0.86



24

miR-30b miR-425 0.91 miR-30c miR-425 0.92 miR-320 miR-425 0.88 miR-324-3p miR-425 0.93 miR-328 miR-425 0.87 miR-331-3p miR-425 0.89 miR-342-3p miR-425 0.91 miR-375 miR-425 0.91 miR-376a miR-425 0.86 let-7d miR-451 0.88 miR-106b miR-451 0.87 miR-122 miR-451 0.99 miR-139-5p miR-451 0.88 miR-192 miR-451 0.88 miR-19b miR-451 0.86 miR-204 miR-451 0.89 miR-20a miR-451 0.92 miR-20b miR-451 0.90 miR-26a miR-451 0.94 miR-324-3p miR-451 0.86 miR-339-3p miR-451 0.86 miR-374a miR-451 0.90 miR-375 miR-451 0.92 miR-143 miR-483-5p 0.97 miR-146a miR-483-5p 0.87 miR-191 miR-483-5p 0.86 miR-222 miR-483-5p 0.85 miR-320 miR-483-5p 0.90 miR-106a miR-484 0.89 miR-126 miR-484 0.91 miR-140-5p miR-484 0.92 miR-143 miR-484 0.90 miR-145 miR-484 0.85 miR-146a miR-484 0.96 miR-150 miR-484 0.89 miR-17 miR-484 0.89 miR-181a miR-484 0.89 miR-186 miR-484 0.86 miR-191 miR-484 0.87 miR-197 miR-484 0.86 miR-222 miR-484 0.99 miR-223 miR-484 0.89 miR-24 miR-484 0.89 miR-25 miR-484 0.86 miR-28-3p miR-484 0.93 miR-28-5p miR-484 0.88 miR-30c miR-484 0.86 miR-320 miR-484 0.99 miR-328 miR-484 0.88 miR-330-3p miR-484 0.89 miR-342-3p miR-484 0.91 miR-425 miR-484 0.86



25

miR-483-5p miR-484 0.91 miR-101 miR-486-3p 0.93 miR-138 miR-486-3p 0.98 miR-198 miR-486-3p 0.96 miR-331-5p miR-486-3p 0.94 let-7d miR-486-5p 0.91 miR-106a miR-486-5p 0.88 miR-126 miR-486-5p 0.91 miR-139-5p miR-486-5p 0.91 miR-146b-5p miR-486-5p 0.90 miR-150 miR-486-5p 0.89 miR-193b miR-486-5p 0.90 miR-197 miR-486-5p 0.88 miR-19b miR-486-5p 0.92 miR-204 miR-486-5p 0.92 miR-223 miR-486-5p 0.85 miR-24 miR-486-5p 0.90 miR-29b miR-486-5p 0.85 miR-30b miR-486-5p 0.85 miR-324-3p miR-486-5p 0.85 miR-342-3p miR-486-5p 0.91 miR-425 miR-486-5p 0.89 miR-103 miR-491-5p 0.92 miR-106b miR-491-5p 0.86 miR-140-3p miR-491-5p 0.92 miR-148a miR-491-5p 0.94 miR-221 miR-491-5p 0.92 miR-370 miR-491-5p 0.93 miR-374b miR-491-5p 0.97 miR-27a miR-494 0.97 miR-27a miR-495 0.95 miR-494 miR-495 0.97 miR-335 miR-500 0.90 miR-361-5p miR-500 0.93 miR-1 miR-501-5p 0.95 miR-101 miR-502-3p 0.98 miR-138 miR-502-3p 0.90 miR-198 miR-502-3p 0.87 miR-331-5p miR-502-3p 1.00 miR-486-3p miR-502-3p 0.94 miR-101 miR-517a 0.99 miR-138 miR-517a 0.92 miR-331-5p miR-517a 0.97 miR-486-3p miR-517a 0.92 miR-502-3p miR-517a 0.97 miR-101 miR-519e 0.99 miR-138 miR-519e 0.90 miR-198 miR-519e 0.87 miR-331-5p miR-519e 1.00 miR-486-3p miR-519e 0.94 miR-502-3p miR-519e 1.00 miR-517a miR-519e 0.97



26

miR-1 miR-520d-5p 0.90 miR-23a miR-520d-5p 0.96 let-7e miR-532-3p 0.94 miR-142-3p miR-532-3p 0.95 miR-17 miR-532-3p 0.87 miR-185 miR-532-3p 0.96 miR-186 miR-532-3p 0.86 miR-19a miR-532-3p 0.90 miR-30b miR-532-3p 0.88 miR-30c miR-532-3p 0.86 miR-331-3p miR-532-3p 0.91 miR-345 miR-532-3p 0.94 miR-339-3p miR-532-5p 0.86 miR-103 miR-539 0.92 miR-106b miR-539 0.86 miR-140-3p miR-539 0.93 miR-148a miR-539 0.93 miR-221 miR-539 0.92 miR-370 miR-539 0.93 miR-374b miR-539 0.97 miR-491-5p miR-539 1.00 miR-454 miR-548a-3p 0.89 miR-146b-5p miR-574-3p 0.99 miR-150 miR-574-3p 0.96 miR-29b miR-574-3p 0.98 miR-342-3p miR-574-3p 0.93 miR-486-5p miR-574-3p 0.92 miR-103 miR-598 0.93 miR-106b miR-598 0.88 miR-140-3p miR-598 0.92 miR-148a miR-598 0.98 miR-193a-5p miR-598 0.86 miR-221 miR-598 0.95 miR-370 miR-598 0.97 miR-374b miR-598 0.99 miR-491-5p miR-598 0.98 miR-539 miR-598 0.98 miR-101 miR-625 0.98 miR-138 miR-625 0.89 miR-198 miR-625 0.88 miR-331-5p miR-625 1.00 miR-486-3p miR-625 0.94 miR-502-3p miR-625 1.00 miR-517a miR-625 0.96 miR-519e miR-625 1.00 miR-129-3p miR-629 0.94 miR-28-5p miR-629 0.93 miR-330-3p miR-629 0.89 miR-10b miR-636 0.90 miR-1 miR-652 0.90 miR-100 miR-660 0.90 miR-146a miR-660 0.88



27

miR-15b miR-660 0.91 miR-16 miR-660 0.85 miR-186 miR-660 0.88 miR-197 miR-660 0.89 miR-19a miR-660 0.86 miR-19b miR-660 0.87 miR-204 miR-660 0.86 miR-30c miR-660 0.88 miR-324-3p miR-660 0.90 miR-330-3p miR-660 0.86 let-7b miR-885-5p 0.92 let-7d miR-885-5p 0.95 miR-122 miR-885-5p 0.88 miR-204 miR-885-5p 0.86 miR-451 miR-885-5p 0.87 miR-486-5p miR-885-5p 0.93 let-7e miR-886-3p 0.90 miR-142-3p miR-886-3p 0.93 miR-17 miR-886-3p 0.86 miR-185 miR-886-3p 0.90 miR-186 miR-886-3p 0.88 miR-197 miR-886-3p 0.85 miR-19a miR-886-3p 0.90 miR-223 miR-886-3p 0.86 miR-30b miR-886-3p 0.92 miR-30c miR-886-3p 0.87 miR-331-3p miR-886-3p 0.87 miR-345 miR-886-3p 0.90 miR-532-3p miR-886-3p 0.95 let-7d miR-886-5p 0.91 miR-103 miR-886-5p 0.91 miR-106a miR-886-5p 0.88 miR-106b miR-886-5p 0.95 miR-122 miR-886-5p 0.86 miR-126 miR-886-5p 0.88 miR-127-3p miR-886-5p 0.92 miR-133a miR-886-5p 0.88 miR-139-5p miR-886-5p 0.93 miR-145 miR-886-5p 0.90 miR-15b miR-886-5p 0.89 miR-17 miR-886-5p 0.89 miR-192 miR-886-5p 0.96 miR-193a-5p miR-886-5p 0.87 miR-193b miR-886-5p 0.96 miR-197 miR-886-5p 0.92 miR-19b miR-886-5p 0.95 miR-204 miR-886-5p 0.96 miR-20a miR-886-5p 0.98 miR-20b miR-886-5p 0.89 miR-21 miR-886-5p 0.95 miR-223 miR-886-5p 0.93 miR-24 miR-886-5p 0.94



28

miR-25 miR-886-5p 0.86 miR-26a miR-886-5p 0.87 miR-30b miR-886-5p 0.94 miR-30c miR-886-5p 0.91 miR-324-3p miR-886-5p 0.94 miR-328 miR-886-5p 0.85 miR-331-3p miR-886-5p 0.89 miR-375 miR-886-5p 0.99 miR-423-5p miR-886-5p 0.90 miR-425 miR-886-5p 0.92 miR-451 miR-886-5p 0.89 miR-486-5p miR-886-5p 0.86 miR-101 miR-9 0.89 miR-10b miR-9 0.86 miR-129-3p miR-9 0.92 miR-198 miR-9 0.86 miR-224 miR-9 0.86 miR-331-5p miR-9 0.94 miR-486-3p miR-9 0.87 miR-502-3p miR-9 0.95 miR-517a miR-9 0.86 miR-519e miR-9 0.94 miR-625 miR-9 0.95 let-7e miR-92a 0.92 miR-106a miR-92a 0.94 miR-106b miR-92a 0.86 miR-126 miR-92a 0.96 miR-127-3p miR-92a 0.87 miR-133a miR-92a 0.93 miR-139-5p miR-92a 0.87 miR-140-5p miR-92a 0.93 miR-145 miR-92a 0.95 miR-146a miR-92a 0.91 miR-15b miR-92a 0.89 miR-16 miR-92a 0.89 miR-17 miR-92a 0.99 miR-181a miR-92a 0.89 miR-185 miR-92a 0.87 miR-186 miR-92a 0.95 miR-192 miR-92a 0.91 miR-193a-5p miR-92a 0.90 miR-193b miR-92a 0.95 miR-197 miR-92a 0.98 miR-19a miR-92a 0.93 miR-19b miR-92a 0.96 miR-204 miR-92a 0.95 miR-20a miR-92a 0.85 miR-21 miR-92a 0.91 miR-222 miR-92a 0.92 miR-223 miR-92a 0.99 miR-24 miR-92a 0.98 miR-25 miR-92a 0.88



29

miR-28-3p miR-92a 0.89 miR-30b miR-92a 0.98 miR-30c miR-92a 0.97 miR-320 miR-92a 0.91 miR-324-3p miR-92a 0.92 miR-328 miR-92a 0.94 miR-331-3p miR-92a 0.97 miR-342-3p miR-92a 0.90 miR-345 miR-92a 0.87 miR-375 miR-92a 0.89 miR-423-5p miR-92a 0.93 miR-425 miR-92a 0.94 miR-484 miR-92a 0.90 miR-486-5p miR-92a 0.89 miR-532-3p miR-92a 0.87 miR-886-3p miR-92a 0.90 miR-886-5p miR-92a 0.92 let-7e miR-93 0.87 miR-142-3p miR-93 0.88 miR-181a miR-93 0.94 miR-328 miR-93 0.85 miR-345 miR-93 0.85 miR-532-3p miR-93 0.86 miR-106a miR-99b 0.89 miR-125a-5p miR-99b 0.91 miR-127-3p miR-99b 0.90 miR-139-3p miR-99b 0.93 miR-139-5p miR-99b 0.86 miR-20b miR-99b 0.91 miR-21 miR-99b 0.91 miR-25 miR-99b 0.90 miR-26a miR-99b 0.90 miR-323-3p miR-99b 0.91 miR-324-3p miR-99b 0.86 miR-425 miR-99b 0.91



30

Online Table IV. miRNA network topology values

ID Node degree

Clustering coefficients

Betweenness centrality

Clusters

miR-197 46 0.6087 294.6777 1 miR-223 46 0.61739 220.8167 1 miR-92a 46 0.6 2.50E+02 1 miR-17 45 0.61414 223.9829 1 miR-30c 45 0.61616 275.9978 1 miR-145 43 0.6268 232.1945 1 miR-24 43 0.67331 137.052 1 miR-425 43 0.6124 922.3542 1 miR-204 42 0.60511 474.7849 1 miR-193b 41 0.66463 149.1595 1 miR-19b 41 0.65732 314.4007 1 miR-30b 41 0.64024 240.3027 1 miR-106a 40 0.6359 727.1196 1 miR-331-3p 40 0.65 165.9824 1 miR-324-3p 39 0.68961 207.2898 1 miR-126 38 0.66999 498.0567 1 miR-192 38 0.69417 210.0613 1 miR-328 38 0.6074 3.84E+02 1 miR-186 37 0.63063 171.1418 1 miR-21 36 0.73492 74.2007 1 miR-886-5p 36 0.71746 1.49E+02 1 miR-106b 35 0.61849 546.8299 1 miR-133a 34 0.74866 82.9921 1 miR-375 34 0.74153 113.1221 1 miR-423-5p 34 0.70232 60.4924 1 miR-127-3p 33 0.76894 46.5204 1 miR-15b 32 0.71573 178.5295 1 miR-103 31 0.60215 398.927 3 miR-140-5p 31 0.70968 79.5007 1 miR-193a-5p 31 0.66452 157.2165 1 miR-25 30 0.72184 166.843 1 miR-19a 29 0.67488 78.6356 1 miR-20a 28 0.7619 67.0426 1 miR-222 28 0.61111 762.8777 6 miR-139-5p 27 0.70655 103.4128 1 miR-146a 27 0.61254 385.378 6 miR-28-3p 27 0.74359 88.0549 1 miR-320 27 0.57835 5.96E+02 6 miR-484 26 0.58769 5.49E+02 6 miR-139-3p 24 0.69928 161.9982 1 miR-20b 22 0.71429 146.5313 1 miR-486-5p 21 0.57143 347.002 4 let-7e 20 0.62632 474.383 1 miR-181a 20 0.64211 106.4101 1 miR-342-3p 20 0.58421 316.9526 4 miR-16 19 0.87719 12.605 1 miR-185 17 0.85294 5.948 1



31

let-7d 16 0.59167 262.511 7 miR-451 16 0.61667 440.929 9 miR-142-3p 15 0.77143 15.0857 1 miR-370 15 0.59048 8.61E+01 3 miR-26a 14 0.62637 152.4076 0 miR-345 14 0.76923 13.9276 1 miR-376a 14 0.78022 52.9869 1 miR-886-3p 14 0.87912 2.37E+00 1 miR-532-3p 13 0.82051 9.24E+00 1 miR-28-5p 12 0.51515 2613.8708 11 miR-660 12 0.68182 7.81E+02 0 miR-99b 12 0.62121 1.38E+02 12 miR-122 11 0.74545 13.0798 9 miR-150 11 0.58182 93.0062 4 miR-374b 11 0.76364 17.2521 3 miR-9 11 0.47273 2.43E+03 2 miR-140-3p 10 0.53333 39.3779 3 miR-221 10 0.8 9.8385 3 miR-598 10 0.84444 7.06E+00 3 miR-331-5p 9 0.91667 2.63E+01 2 miR-486-3p 9 0.91667 26.3214 2 miR-491-5p 9 0.91667 3.4064 3 miR-502-3p 9 0.91667 2.63E+01 2 miR-519e 9 0.91667 2.63E+01 2 miR-539 9 0.91667 3.41E+00 3 miR-625 9 0.91667 2.63E+01 2 miR-101 8 0.96429 25.75 2 miR-138 8 0.92857 0.57143 2 miR-148a 8 0.96429 0.44653 3 miR-330-3p 8 0.46429 1.03E+03 11 miR-517a 8 0.96429 25.75 2 miR-191 7 0.42857 438.6377 5 miR-198 7 0.95238 25.75 2 miR-199a-3p 7 0.66667 11.8802 1 miR-146b-5p 6 0.8 41.3623 4 miR-374a 6 0.6 30.7824 9 miR-483-5p 6 0.86667 3.6722 5 miR-885-5p 6 0.6 36.4249 7 miR-93 6 0.6 2.10E+00 1 miR-129-3p 5 0.3 3478 0 miR-143 5 0.9 3.0345 5 miR-29b 5 1 0 4 miR-574-3p 5 1 0.00E+00 4 miR-1 4 0 866 10 miR-195 3 1 0 1 miR-323-3p 3 1 0.00E+00 12 miR-339-3p 3 0.33333 2.20E+02 0 miR-629 3 1 0.00E+00 11 let-7b 2 1 0 7 let-7c 2 0 220 8 miR-100 2 0 436 8 miR-10b 2 0 220 0



32

miR-125a-5p 2 1 0 12 miR-27a 2 1 0 13 miR-301a 2 0 220 0 miR-335 2 1 0.00E+00 14 miR-361-5p 2 1 0.00E+00 14 miR-494 2 1 0 13 miR-495 2 1 0 13 miR-500 2 1 0.00E+00 14 miR-520d-5p 2 0 220 0 miR-15a 1 0 0 8 miR-224 1 0 0 2 miR-23a 1 0 0 0 miR-29c 1 0 0.00E+00 5 miR-365 1 0 0 0 miR-411 1 0 0 5 miR-454 1 0 0 0 miR-501-5p 1 0 0 10 miR-532-5p 1 0 0.00E+00 0 miR-548a-3p 1 0 0.00E+00 0 miR-636 1 0 0.00E+00 0 miR-652 1 0 0 10



33

Online Figure I. Properties of miRNA co-expression network. A) Probability density

distribution of Pearson correlation coefficients (PCC). Interestingly, there were very few negative

correlations. B) Number of nodes in the miRNA network and C) number of edges in the co-

expression network as a function of PCC. As PCC values increased, weak edges were removed,

while node number remained constant. D) At larger PCC values, the network became modular as

evidenced by the decreasing but large clustering coefficient. E) Network information flow

described by the average eigenvector centrality. F) Scale-free architecture of the miRNA co-

expression network dominated by a small number of central nodes attached to a large number of

loosely connected miRNAs. These topological features are consistent with the general behavior of

biological networks and topologies detected in protein-protein interaction collections such as

STRING.



Online Figure II. miRNA co-expression network inferred from microarray

experiments for 13 differentially expressed and topologically unique miRNAs. Of

the 30 differentially expressed miRNAs (blue), 13 miRNAs (red) were selected by

probing their topological properties in a co-expression network, inferred using

Pearson Correlation Coefficients (PCC), as opposed to individual over- or under-

expression. Significant miRNAs co-expressions are represented as network edges.



35

Online Figure III. MiRNA networks. A) Differential network structure between 13

miRNAs in controls (n=91) and manifest DM (n=56). Nodes represent individual

miRNAs and edges (links) represent the extent of expression similarity measured

using the Context likelihood of relatedness algorithm. Control (13 nodes, 25 links)

and DM (13 nodes, 19 links) networks shared only 10 links. The disease state was

characterized by substantial edge rewiring (miR-15a). B) Differential topology of

control and DM networks. The control network (green bars) was characterized by a

larger node degree, clustering coefficient and eigenvector centrality than the one in

DM (red bars).

B.

A.



36

Online Figure IV. High glucose leads to selective decrease in miRNA content in

endothelial derived apoptotic bodies. The effect of increased glucose on the miRNA

content of endothelial derived apoptotic bodies were assessed using qPCR. miR-454 was

used as a normalization control. Data shown are of four independent experiments and

presented as means SEM, * p<0.05



plasma microrna profiling reveals loss of endothelial mir

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